Great video, love to see more like this. Automating games like this is an amazing way to introduce people to OpenCV, it's simple to explain but teaches you important skills applicable to a much wider range of tasks. I'm glad I randomly stumbled upon your channel, your videos don't get nearly as many views as it deserves for such high quality educational content.
i bascily became a programmer by starting to atuomate games. learned many skills from basic programming to ocr to stock market theroies to reinforcement learning while doing that.
To circumvent the missed image detection from a day/night cycle, you can add a desaturation to both your sample and comparison images to grayscale them before comparison. This usually works for pixel-based art styles, as day/night is usually just an added color filter over the original image. The exception being those games that use specular or bloom lighting effects, which can distort the end-result grayscale in the image. The trade off, however, is that the added step of desaturating the sample image on each frame will slow down the script a bit. EDIT: This method also wouldn't work in games that reuse sprites with different color palettes, for obvious reasons.
Differentiate objects by color is a cost effective way of expanding the object types in game. Red goblins are fire goblins. Blue goblins are ice goblins. If you want to use flame thrower on red goblins, and water gun on blue goblins, you need to be able to determine type you're identifying. That's the issue discussed above.
15:15 A more efficient solution here would be to just check for rectangles with intersecting regions. Not sure about python but in c# this is very simple with the Rect.IntersectsWith method (you can also just do it manually, the math is easy). Then you can combine them by inflating one rect with the difference from the other. Also for more reliable matching, there are various imaging algorithms you can use, for my OCR projects I do: grayscale > scaling > binarization > inversion > denoise > bordering, this helps a lot for matching foreground objects over varying backgrounds. You can also start with colour averaging which can make scanning for objects significantly faster at higher resolutions because you can scan chunks of the image and skip processing any that aren't similar. I've used these methods for overlaying real-time translation of text in non-english games.
Amazing work! Thank you so much for sharing this! I would love to see a video on how to implement convolutional neural networks to do object recognition.
You could have also done the grouping by comparing the distances of all rectangle centroids which would essentially create a node graph with every center connected to everyother center and then combining all nodes whose distance is below some threshold distance. Your solution works, I just think it’s good practice to use more general algorithms.
Here's an idea to get around the different shades thing: transform all target images to black and white, and same with the recording output going into the program.
@@gnack420 Shades imply there's color. What you wanted to say was value (lightdark). Sorry I got into definitions. But yeah, you're right. I wrote that comment before finishing the video, I didn't know you were gonna use an algorithm to find likely matches, I thought that whould require some deep learning or something much more advanced. Shows how much I know about programming. Oh, and btw, thanks for the video, it was really fun!
Thanks I work really hard on trying to figure out the best pace to keep people engaged and still not skip topics. I will continue to try and improve. Thanks for commenting and watching.
Ah thank you so much, i was looking for a tutorial like this for a very long time :) I did something similiar in auto it just for fun, but I always wanted do something like that in a "real" programming language with more powerful libraries. Thank you so much =) I only need to learn how to use it in 3d games /video capturing. But it is just fine to learn right from the start :)
@@ClarityCoders I already did :) although apparently the only way to grow small channels these days is to leave comments on a bunch of related videos so people click on your profile.
I love to see you doing these videos! I’d like to see one that is based on real pictures, like “is the car pointed left or right” etc and incorporate some training and AI
Oh, come on.. I just decided "Ah crap, just get started..(!) Ima start with the basic webstack and see from there. And then I stumbled over this channel and THIS video.. Great video @ClarityCoders!
Hey bro, you can google mines game usually available in rummy apps. How to create mines game bot? To make all cells visible by seeing all hidden covered mines inside cells/grid or uncover then through any method or using OpenCv(image recognition) algorithm method to identify exact mines in the cells/grid? Can you make that tutorial?
Pretty clear and very interesting, coming from C and learning Python and opencv for industrial purpose, you helped me a lot , template matching can be used in so many way in my work. you have all my respect and i'll follow you with great joy. Thanks again for your videos.
Hi brother is it possible for you to make a chess bot with opencv as u make for other games or for knife hit game if yes please make a video on it .It will be really helpful .
I love this video and the idea, I don't know anything about coding but if you would every take a look at the game called "Parking master multiplayer 2" (the game requires a lot of repetition plays in order to have money, I would love to see you make a video about that game of how you would set up for it to auto drive the car into the parking spot!!
Amazing tutorial although I do have some ideas to improve some of what was presented, Firstly the rectangles grouping section, I'm sure there's a better way than just duplicating the list, maybe manually comparing the x, y of rectangles and if they are similar to another rectangle we don't use it The other point would be about beating the highscore, i would test for a single pixel's color above the player on each side where the background is static and check if it's color changes (a branch is above) and move accordingly
You can also find the wheat points without overlaps by running a local maxima filter on the grayscale image- accomplished in OpenCV with a dilate filter followed by a compare filter. You might not need it for this use-case, but you can also additionally filter out plateaus of local maximum value with an erode and a compare (if you want to know what to compare against what, for the sake of brevity here either google it or just try a few combinations; heck, you don’t need Jupyter to figure out the correct operations; you can prototype this kind of stuff with Photoshop/Gimp layers easily). I like image-processing solutions like this because 1. For an end-use you can more easily run the whole thing on a GPU where operations over a whole image are cheap and reducing that an array of numerical results is the expensive part, and 2. You can visually see and tune/debug the dilated image, the dilated-compared image, the dilated-compared-eroded image, and the dilated-compared-eroded-compared image.
Your score has been topped! No template matching was needed since the game uses the exact same pixels in the same locations but still great to know that functionality exists within OpenCV. keep on keepin on.
Nice; Solid introductory video! I enjoyed watching. Wish there was a fast & efficient template matching method that worked with a high dimensional image space. I imagine the game you tested in the vid was only 800x600 or something lol. When working with large images I usually have to search a small section or it will take too long to compute.
For sure I almost always cut down the area where I'm taking the screen shots. Especially if it's a real time thing where time matters. Thanks for watching and commenting I really appreciate it.
@TridentflayerThe other thing you can attempt to do is vectorize your code very heavily so that you can do all of your calculations in numpy operations. Speaking from miserable experience, that can be far harder than just biting the bullet and doing it in c++
about kick ya chop, u dont have to use entire detection system as u did with opencv, wastefull, slow. u can avchieve same result by just sticking to 1 backround pixel with 2 lines of code at max
Thank you very much my friend, first of all, I follow the wheat finding code exactly and it doesn't work. Can you send it as a working project rather than a tutorial?
TNice tutorials video is a great introduction to soft soft for beginners. I would Nice tutorialghly recomnd tNice tutorials tutorial to anyone starting out with soft soft.
imshow,imread,and al the rest of the stuff that comes after cv2. isnt working . it says __init__.py isnt found .i reinstalled is 5 times but still nothing
Teacher, first congratulations for the channel. I need your help, I have a simple image with a range of 5 placements where the quantity is identified, how do I identify the biggest color type red and say where the X,Y is, and if you can help me, and only for create an alert.
Это работает для статики. Тут зерно имеет конкретные цвета и никак не меняется. Я пробовал этот метод и он не работает для динамических картинок. Например, на экране идет снег, и снежинки закрывают объект, задний фон объекта меняется.
I would agree if you just want to quick automate something there are better routes! You can however build on this into full NN that have endless possibilities. Thanks for watching I really appreciate it.
Oh, this might solve a problem I have. There’s some made up alphabet which looks like it was made with a fixed typeface, and I want to transcribe the text in the images into actual text in order to try to decipher it, and I think I know how to extract the characters, but I still need to find how to detect which character they are. I can’t use standard OCR because these are a made up alphabet in an Easter egg for a game.
Could this tecnique work to detect parts of a document (for example a rectangle with a text) in order to read what's inside that section of the document? It would be a scanned document so it could arrive with horizontal lines not perfectly aligned due the subtle movements of the paper durinig the passage under the scanner.
I think you can make it much easier. OpenCV can detect rectangles in image. Next, it can detect text (OCR) within those rectangles. If rectangles are not perfectly aligned you can fix perspective of those rects in openCV too.
This is a great tutorial - thanks! Could you also do one explaining the kick ya chop script you have in your git hub? Also I tried to use the kick ya chop script but had to increase the sleep time to around 0.2 otherwise it wouldn't work. This is even after I tried reducing the region to search in. What gives? Do I need a faster computer or something?
This is AWESOME and it has been extremely helpful to me. There is one thing I'm trying to figure out. Let's say I grab an image and I know I want to look for one "needle" in the lower half of the image and a second in the upper half of the image and I want to know the relationship of the matches to each other. Now one way I could do this is grab two different regions two images. Do the matches, and then use some math to figure out their relationship to each other. But, what would be really convenient is if I can just look for the matches I need to in the lower half the image and get, multiple matches and then look for the other needle in the upper half and get multiple matches and already have the x and y coordinates for the overall image without having to translate them. If it can't be done, it's easy enough to add y offset to the coordinates I get out. But I was wondering.
You mean you want to save time by only looking in the correct regions of the images while searching? You could use slicing to accomplish this task. Google python slicing.
Hi i am beginner, i am preparing script for a similar game but the question is can i run script like this for multiple game windows lets say arranged in 3x3 matirx (just like tic tac toe) on desktop and would it work or do i need to implement something more?
I'm pretty sure there are a lot of better and easier ways to prevent duplicate/overlapping rectangles, but grouping them is way more taxing and complicated than just filtering them out.
A better way to deal with multiple matches corresponding to a single item is to use a local maximum finder. scikit-image's peak_local_max is one such possibility.
How to take screenshot and use it as a variable instead of writing it to file and reading it from the file. The issue I have is that first, I'm afraid that my harddrive age won't last that long with this method and second, it is faster
Check out the code on the github for kick ya chop. I do exactly that! github.com/ClarityCoders/ComputerVision-OpenCV/blob/master/Lesson3-TemplateMatching/PlayGame.py
![[#2024MAMA] ROSÉ (로제), Bruno Mars - APT. | Mnet 241122 방송](http://i.ytimg.com/vi/dgGqD28J6aQ/mqdefault.jpg)
Great video, love to see more like this. Automating games like this is an amazing way to introduce people to OpenCV, it's simple to explain but teaches you important skills applicable to a much wider range of tasks. I'm glad I randomly stumbled upon your channel, your videos don't get nearly as many views as it deserves for such high quality educational content.
Glad you enjoyed it! I'll have more coming soon!
I agree, I had my first coding experience from minecraft because I wanted to automate a turtle in the modded game xD
@@yichong777 Thanks for the comment it means a lot. I was getting beat up a bit today haha...
i bascily became a programmer by starting to atuomate games. learned many skills from basic programming to ocr to stock market theroies to reinforcement learning while doing that.
@@bobchelios9961 So did i....... which is why it's kind of a shame some games are so quick to ban.
To circumvent the missed image detection from a day/night cycle, you can add a desaturation to both your sample and comparison images to grayscale them before comparison.
This usually works for pixel-based art styles, as day/night is usually just an added color filter over the original image.
The exception being those games that use specular or bloom lighting effects, which can distort the end-result grayscale in the image.
The trade off, however, is that the added step of desaturating the sample image on each frame will slow down the script a bit.
EDIT: This method also wouldn't work in games that reuse sprites with different color palettes, for obvious reasons.
Yes sir! Very good points this is something I've used in a few projects and probably should have talked about! Great comment.
hey could you help make a open cv for shooting the ball in nba 2k
I didn’t get it why do they use different color palettes for different reasons?
Differentiate objects by color is a cost effective way of expanding the object types in game.
Red goblins are fire goblins.
Blue goblins are ice goblins.
If you want to use flame thrower on red goblins, and water gun on blue goblins, you need to be able to determine type you're identifying.
That's the issue discussed above.
15:15 A more efficient solution here would be to just check for rectangles with intersecting regions. Not sure about python but in c# this is very simple with the Rect.IntersectsWith method (you can also just do it manually, the math is easy). Then you can combine them by inflating one rect with the difference from the other.
Also for more reliable matching, there are various imaging algorithms you can use, for my OCR projects I do: grayscale > scaling > binarization > inversion > denoise > bordering, this helps a lot for matching foreground objects over varying backgrounds. You can also start with colour averaging which can make scanning for objects significantly faster at higher resolutions because you can scan chunks of the image and skip processing any that aren't similar. I've used these methods for overlaying real-time translation of text in non-english games.
Amazing work! Thank you so much for sharing this! I would love to see a video on how to implement convolutional neural networks to do object recognition.
It's on my list for sure!
You could have also done the grouping by comparing the distances of all rectangle centroids which would essentially create a node graph with every center connected to everyother center and then combining all nodes whose distance is below some threshold distance. Your solution works, I just think it’s good practice to use more general algorithms.
I would agree very good points. Thanks for watching and commenting.
Here's an idea to get around the different shades thing: transform all target images to black and white, and same with the recording output going into the program.
Different colours will end up as different shades of grey though. The correct approach is what the library already does, which is normalisation.
@@gnack420 Shades imply there's color. What you wanted to say was value (lightdark). Sorry I got into definitions. But yeah, you're right. I wrote that comment before finishing the video, I didn't know you were gonna use an algorithm to find likely matches, I thought that whould require some deep learning or something much more advanced. Shows how much I know about programming. Oh, and btw, thanks for the video, it was really fun!
Your videos are awesome man! I really love them :D
Mean a lot thanks. I really appreciate the view and comment have a good one.
3:34 "now my hope is that we detect multiple instances of weed"
yes pls!
except he clearly says wheat
@@NoshNosher are you sure about that bro?
@@NoshNosher Charles Shwab ova here
@@Beatsbasteln I am 100% sure he said wheat.
@@emifro but how are you going to smoke wheat?
This is a really well paced and detailed guide! Great work :)
Thanks I work really hard on trying to figure out the best pace to keep people engaged and still not skip topics. I will continue to try and improve. Thanks for commenting and watching.
man!!!!
your are amazing
we need more of this content with this type of teaching methods
Thank for the examples and how it all works, liked and subbed.
Thank you man, this is awesome !!
Glad you liked it thanks for watching!
Ah thank you so much, i was looking for a tutorial like this for a very long time :) I did something similiar in auto it just for fun, but I always wanted do something like that in a "real" programming language with more powerful libraries. Thank you so much =)
I only need to learn how to use it in 3d games /video capturing. But it is just fine to learn right from the start :)
Great tutorial, really enjoy and appreciate you explain what each line does in detail. Subscribed and liked!
haha this is awesome, i've thought about doing it before and after this i might have to. One of the most relatable/interesting coding videos lmao.
glad you liked it! I hope you do please share it if you do.
@@ClarityCoders I already did :) although apparently the only way to grow small channels these days is to leave comments on a bunch of related videos so people click on your profile.
@@stevesteverson3345 Trying to grow your channel?
@@ClarityCoders hahah yeah come watch any of my 0 videos
I love to see you doing these videos! I’d like to see one that is based on real pictures, like “is the car pointed left or right” etc and incorporate some training and AI
Cool idea! I'll put it on my list.
Oh, come on.. I just decided "Ah crap, just get started..(!) Ima start with the basic webstack and see from there.
And then I stumbled over this channel and THIS video..
Great video @ClarityCoders!
thanks man. I love your teaching style
Teaching archivement unlocked! congrats man! you are helping people from brazil!
I am from a tiny town in the US never thought people would watch me in Brazil. Thanks for watching and commenting.
@@ClarityCoders 🇧🇷
this is what I have been looking for... THANK YOUUUU
This is an awesome, very straightforward tutorial. Thank you!
Hey bro, you can google mines game usually available in rummy apps. How to create mines game bot? To make all cells visible by seeing all hidden covered mines inside cells/grid or uncover then through any method or using OpenCv(image recognition) algorithm method to identify exact mines in the cells/grid? Can you make that tutorial?
Pretty clear and very interesting, coming from C and learning Python and opencv for industrial purpose, you helped me a lot , template matching can be used in so many way in my work. you have all my respect and i'll follow you with great joy. Thanks again for your videos.
This comment really means a lot to me. Thanks for watching and commenting I'll keep making videos.
Hi brother is it possible for you to make a chess bot with opencv as u make for other games or for knife hit game if yes please make a video on it .It will be really helpful .
Sure let me see what I can do! Hit that bell so you don't miss it.
ohh I already done that as I like your content so much and thanks it really means a lot.
@@grzegorzabedzki2989 awesome work, very readable code, even though I have no interest in chess.
@@ClarityCoders please don't, chess sucks with cheaters. And if you must, at least don't release the code
I love this video and the idea, I don't know anything about coding but if you would every take a look at the game called "Parking master multiplayer 2" (the game requires a lot of repetition plays in order to have money, I would love to see you make a video about that game of how you would set up for it to auto drive the car into the parking spot!!
Here after watching CS Dojo's video :)
Awesome thanks for stopping by!!
Thanks man, you saved my graduation project!
Amazing tutorial although I do have some ideas to improve some of what was presented,
Firstly the rectangles grouping section, I'm sure there's a better way than just duplicating the list, maybe manually comparing the x, y of rectangles and if they are similar to another rectangle we don't use it
The other point would be about beating the highscore, i would test for a single pixel's color above the player on each side where the background is static and check if it's color changes (a branch is above) and move accordingly
Ty very much, i could not find someone explain this as well as you did ngl saved me
Very fun to watch and learned a lot. Thankyou.
Thanks for watching/commenting it means a lot.
best tuto about template match i have ever seen！helpful！
I'm loving your content! As a fellow ML engineer, and fan on mini online games, I love this!
Thanks! I really appreciate the feedback and views!
You can also find the wheat points without overlaps by running a local maxima filter on the grayscale image- accomplished in OpenCV with a dilate filter followed by a compare filter. You might not need it for this use-case, but you can also additionally filter out plateaus of local maximum value with an erode and a compare (if you want to know what to compare against what, for the sake of brevity here either google it or just try a few combinations; heck, you don’t need Jupyter to figure out the correct operations; you can prototype this kind of stuff with Photoshop/Gimp layers easily).
I like image-processing solutions like this because 1. For an end-use you can more easily run the whole thing on a GPU where operations over a whole image are cheap and reducing that an array of numerical results is the expensive part, and 2. You can visually see and tune/debug the dilated image, the dilated-compared image, the dilated-compared-eroded image, and the dilated-compared-eroded-compared image.
Very good points and great feedback. Thanks for watching and commenting.
Couldn't be more clear. Many thanks...
I love the tutorial; keep up the great work! Heads up, I am coming for your high score ;)
I hope you do! Thanks for watching I appreciate it!
Your score has been topped! No template matching was needed since the game uses the exact same pixels in the same locations but still great to know that functionality exists within OpenCV. keep on keepin on.
@@wyatt5984 Yeah I noticed that as well haha! Gives you some flexibility for more complex games though. Nice score!
@@wyatt5984 Our discord is you're into that sort of thing. discord.gg/cAWW5qq
getting game information from memory: 😴😴🤢🤬🤬
getting game information using opencv: 😎😎🤑🤑🥶🥶
Both can be crazy frustrating haha...
Nice; Solid introductory video! I enjoyed watching. Wish there was a fast & efficient template matching method that worked with a high dimensional image space. I imagine the game you tested in the vid was only 800x600 or something lol. When working with large images I usually have to search a small section or it will take too long to compute.
For sure I almost always cut down the area where I'm taking the screen shots. Especially if it's a real time thing where time matters. Thanks for watching and commenting I really appreciate it.
You could also try speeding it up by scaling the image down before performing the template matching.
@@SuperMasterDesaster Yeah I really like this idea as well.
I use IDA Pro to Dominate in Multiplayer Games. In HTML Games I reverse the Server requests and just need a proper parser or memory pattern.
Very good video, can you combine your idea into the online game of chess, and use OPENCV to identify the FEN position code of chess on the web page?
amazing. thanks. so much easy class from you
expected to see dominating that online farming game
Sorrry! Maybe in the next one 😏
Thank you for making this video, it really helps me a lot.
I hope so. Let me know if you have any questions.
Nice video but one question. Did you purposefully excactly double their highscore at the end or was that coincidence?
I didn't even know! Good to have eyes like yours on these videos. Thanks for watching Noah.
Liked and subscribed - explained and shown structured and clearly! Thanks!
Thank you! Very great guide to OpenCV! But how to optimize it to get it to run 100 times faster? How to use multiple CPU cores and GPU with OpenCV?
@TridentflayerThe other thing you can attempt to do is vectorize your code very heavily so that you can do all of your calculations in numpy operations. Speaking from miserable experience, that can be far harder than just biting the bullet and doing it in c++
Awesome video! Learned a lot!
Jupyter us perfect for a live demonstration 👌
I agree. I actually caught a lot of heat for using Jupyter haha...
about kick ya chop, u dont have to use entire detection system as u did with opencv, wastefull, slow. u can avchieve same result by just sticking to 1 backround pixel with 2 lines of code at max
blessed by youtube algo.. found your video and subscribed!
It's actually given me some love this past week. Thanks for watching and commenting.
Thank you very much my friend, first of all, I follow the wheat finding code exactly and it doesn't work. Can you send it as a working project rather than a tutorial?
OOOR in order to get rid of the additional rectangles you could just use sets to make get rid of data repetition
Great Idea.
@claritycoders Thanks fo the videos! May you guys comment on how do games (their developers) catch such bots? Asking for the ways around obviously)
Very useful, thank you for sharing!
Thanks for watching and commenting!
Cool video but if you used vs code you wouldn't need 2/3 of your code to be erroneous functions calls that you just need to keep it from crashing.
Wow, this is so cool! Thanks for sharing!
Thanks for the comment more to come stay tuned.
please your codi, dimensions_left = {
'left': 164,
'top': 92,
'width': 150,
'height': 250
}
dimensions_right = {
'left': 520,
'top': 600,
'width': 150,
'height': 250
} , what config positions the screen corret ? what exemple ?
ty cuz ive been having a hard ti getting started.
Anytime let me know if you have any questions!
TNice tutorials video is a great introduction to soft soft for beginners. I would Nice tutorialghly recomnd tNice tutorials tutorial to anyone starting out with soft soft.
Appreciate it! Thanks for the comment.
3:29 "inside PAINT"???
Dude, just hit Shift+WindowsKey+S and cut out the picture you need :->
Good video tho, really helpful :)
why is my match when copying and pasting from the haystack img 70-86% match instead of 99??? what am i doing wrong?
great job man :D
Thanks I really appreciate it.
Thank You for this valuable video
imshow,imread,and al the rest of the stuff that comes after cv2. isnt working . it says __init__.py isnt found .i reinstalled is 5 times but still nothing
This is awesome thanks for the tutorial!
I just wonder how to implement the code with 5 multiple window (open at the same time)
Teacher, first congratulations for the channel. I need your help, I have a simple image with a range of 5 placements where the quantity is identified, how do I identify the biggest color type red and say where the X,Y is, and if you can help me, and only for create an alert.
Это работает для статики. Тут зерно имеет конкретные цвета и никак не меняется. Я пробовал этот метод и он не работает для динамических картинок. Например, на экране идет снег, и снежинки закрывают объект, задний фон объекта меняется.
This is a huge inspiration.
thanks means a lot!
As a way to learn OpenCV - "why not". However Sikuli is already doing all that. And it's Python-based (one of the options).
I would agree if you just want to quick automate something there are better routes! You can however build on this into full NN that have endless possibilities. Thanks for watching I really appreciate it.
this seems really really cool; I want to do that on forge of empires . I'll watch this at some point
Hope you do! Thanks for the comment.
Oh, this might solve a problem I have. There’s some made up alphabet which looks like it was made with a fixed typeface, and I want to transcribe the text in the images into actual text in order to try to decipher it, and I think I know how to extract the characters, but I still need to find how to detect which character they are.
I can’t use standard OCR because these are a made up alphabet in an Easter egg for a game.
Great Video!
Thanks for watching protect that melon.
Great video, very helpful
Dude, this is so genius. Thx!
ClarityCoders
-very very awesome
Thanks I really appreciate the comment.
@@ClarityCoders DO MORE AWESOME THINGSS)))
I'm imagining, how can I use template matching on GIS software.
that small insect walking across his screen got me
Dang bugs.
Are you taking screenshots from the whole screen or just the browser content?
I always compared images with mean square root or structural similarity. Template matching seem to be more intuitive
Probably similar in speed? Thanks for watching / commenting.
Thank you Mac Miller.
Hahaha love it.
great video! could you make something like this for a pokemon game walking in a grass and leveling up?
Could this tecnique work to detect parts of a document (for example a rectangle with a text) in order to read what's inside that section of the document? It would be a scanned document so it could arrive with horizontal lines not perfectly aligned due the subtle movements of the paper durinig the passage under the scanner.
I think you can make it much easier. OpenCV can detect rectangles in image. Next, it can detect text (OCR) within those rectangles. If rectangles are not perfectly aligned you can fix perspective of those rects in openCV too.
This is a great tutorial - thanks! Could you also do one explaining the kick ya chop script you have in your git hub? Also I tried to use the kick ya chop script but had to increase the sleep time to around 0.2 otherwise it wouldn't work. This is even after I tried reducing the region to search in. What gives? Do I need a faster computer or something?
Yeah it might just be a difference in processing speed. I'll try to get some videos out explaining the code more in depth.
woah you jump from 2k subs to 7k in 5 days, congrats
This works perfectly on VSCode, but as soon as I turn it into an exe with pyinstaller it does nothing.
Great video thank you!
This is AWESOME and it has been extremely helpful to me.
There is one thing I'm trying to figure out. Let's say I grab an image and I know I want to look for one "needle" in the lower half of the image and a second in the upper half of the image and I want to know the relationship of the matches to each other.
Now one way I could do this is grab two different regions two images. Do the matches, and then use some math to figure out their relationship to each other.
But, what would be really convenient is if I can just look for the matches I need to in the lower half the image and get, multiple matches and then look for the other needle in the upper half and get multiple matches and already have the x and y coordinates for the overall image without having to translate them.
If it can't be done, it's easy enough to add y offset to the coordinates I get out. But I was wondering.
You mean you want to save time by only looking in the correct regions of the images while searching? You could use slicing to accomplish this task. Google python slicing.
Pretty nice! Found this on my recommended. Subbed :)
Thanks for the sub / comment means a lot.
Can i work with multiple models of an NPC (different color clothes, but similar image) in 3d? Like multiple images, side, front, back?
Might needs something a little more flexible like a neural network.
Amezing tutorial, subscrubed!
Thank you! Thanks for watching / commenting.
Hi i am beginner, i am preparing script for a similar game but the question is can i run script like this for multiple game windows lets say arranged in 3x3 matirx (just like tic tac toe) on desktop and would it work or do i need to implement something more?
I'm pretty sure there are a lot of better and easier ways to prevent duplicate/overlapping rectangles, but grouping them is way more taxing and complicated than just filtering them out.
Very good points. I'll look into the options and improve the instruction next time. Thanks for watching and commenting.
Is it possible to move the mouse to the location of the identified object on the screen instead of a pre-set point?
In The setup thank you so much!
No problem. Thanks for watching.
bro can you write it as a scipte cause i tryed and it doesn't work like yours the rectongel doesnt showed on the the colored image
A better way to deal with multiple matches corresponding to a single item is to use a local maximum finder. scikit-image's peak_local_max is one such possibility.
Good idea. I'll check it out.
How to take screenshot and use it as a variable instead of writing it to file and reading it from the file. The issue I have is that first, I'm afraid that my harddrive age won't last that long with this method and second, it is faster
Check out the code on the github for kick ya chop. I do exactly that! github.com/ClarityCoders/ComputerVision-OpenCV/blob/master/Lesson3-TemplateMatching/PlayGame.py
Funny thing is, really early Ultima Online "autopilots" used image matching like this. Might have even predated OpenCV ...
Yup!
Outstanding!
2nd year cs student - these videos are awesome keep it up!!
Instead of trying to group rectangles together, why not just find the local maximas of the correlation values?